#### PyNN implementation of benchmarks 1 and 2

from the paper
Brette R, Rudolph M, Carnevale T, Hines M, Beeman D, Bower JM, Diesmann M, Morrison A, Goodman PH, Harris Jr. FC, Zirpe M, Natschlager T, Pecevski D, Ermentrout B, Djurfeldt M, Lansner A, Rochel O, Vieville T, Muller E, Davison AP, El Boustani S and Destexhe A. Simulation of networks of spiking neurons: A review of tools and strategies. Journal of Computational Neuroscience, vol 23, p 349-398, 2007

##### Obtaining and installing PyNN

Download the latest source distribution from the PyNN download page, then run the setup script, e.g.:

      $ tar xzf PyNN-0.4.0.tar.gz
      $ cd PyNN-0.4.0
      $ python setup.py install

For more detailed installation instructions, and the full users ' guide, go to http://neuralensemble.org/PyNN.

##### Running the simulations:

Change to the directory corresponding to the version of PyNN that you have then run:

      $ python VAbenchmarks.py <simulator> <benchmark>

<simulator> is either neuron, nest1, nest2, or pcsim>
<benchmark> is either CUBA or COBA.

This will create a subdirectory 'Results' and write the datafiles in it.

##### Plotting results

(requires matplotlib and NeuroTools)

      $ python VAbenchmarks.py <benchmark> neuron nest2 pcsim

If you didn't use a particular simulator, remove it from the argument list.

This will create a figure in PNG format in the Results directory. The figures should look something like this: